Occupational health risk to nanoparticulate exposure

Abstract

The evolution of nanotechnology from laboratory research to full-scale production has led to the need to understand the health risk to workers in that industry from the dispersion of nanoparticles escaping from various aspects of the production process. Risk is a function of both the hazard imposed by a compound or material and the expected exposure level. Therefore, research to evaluate proper exposure assessment methods specific to nanoparticles in a workplace atmosphere, as well as research on the toxicological properties of nanoparticles, has been conducted to better understand methods for protecting the health of workers in this burgeoning industry. From an assessment standpoint, researchers are evaluating both the accuracy and validity of currently available instruments and the merits of each of the three metrics – mass, surface area, and count – as indicators of exposure that provide the most relevant indication of worker health risk. Likewise, toxicologists are employing both in vitro and in vivo methods to understand the potential hazard to workers who may inhale aerosolized nanoparticles. This review provides an overview of current research efforts in nanoparticle exposure assessment and toxicology with an emphasis on how information from both fields of study combine to provide guidance to minimize the health risk posed by nanoparticulate exposure in the workplace.

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Patrick T. O'Shaughnessy

Patrick T. O'Shaughnessy is a Professor in the Department of Occupational & Environmental Health with a joint appointment in Civil and Environmental Engineering at The University of Iowa where he has served on the faculty for the past 15 years. Dr O'Shaughnessy is a recognized scholar in the field of aerosol physics and human exposure assessment applied to occupational and environmental health concerns. His current research is associated with developing assessment methods for nanoparticles in the workplace, analyzing dust exposures relative to tasks performed in agricultural operations, evaluating the effectiveness of respirators in humid environments, and modeling the dispersion of contaminants from agricultural buildings.

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Environmental impact

The purposeful creation of particles at the nanometer level has the potential to cause harm to aspects of the outdoor environment as well as undesired health effects among people in indoor environments. The most likely worst-case scenario for indoor environments is among workers in production facilities that create large quantities of nanopowders and who may be adversely affected by fugitive emissions of the powders as an aerosol dispersed throughout the workplace. This article addresses the many issues associated with that scenario and therefore will have an impact on future research needed to properly assess nanoparticle exposures as well as toxicological investigations to relate nanoparticle exposure to health effects.

Introduction

Aerosols with at least one dimension <100 nm, or “ultrafine” particles,¹ are known to exist in both the ambient and indoor environments. They typically result from combustion processes in which the hot vapour condenses into primary particles and quickly coagulate into chain aggregates. However, with the advent of industrial methods purposely designed to mimic this process, as well as others to create ultrafine particles, a new classification of aerosol that also has at least one dimension <100 nm, nanoparticles, has arisen over the past decade. With this new technology, rather than the “incidental” ultrafine particle there now exists the potential that purposely created “engineered” nanoparticles may escape from a production plant to contribute to other ultrafines in the atmosphere, or remain within the plant and contaminate indoor air. This second scenario is the focus of this review as it constitutes an exposure event to workers in a plant at concentration levels that will necessarily exceed those created outdoors and may create a human health risk.

The current, rapid expansion of industries that produce and utilize nanoparticles has created a need to thoroughly determine how the production of these particles will pose a health or safety threat to the workers involved. Although the number of industries associated with nanoparticle creation or use is still relatively small, the industry is expected to grow rapidly and therefore create a significant number of workers at risk of exposure to these particles. The purpose of this review is to summarize the current state of knowledge of nanoparticles as they pose a health hazard to workers by the inhalation route. Although the risk of acquiring an ill-health effect from exposure to nanoparticles can be mitigated by the implementation of control devices such as filters and ventilation, this review will emphasize the health issues and assessment techniques associated with nanoparticle exposures in workplaces rather than control techniques. Furthermore, this review was written to “cross the bridge” between researchers with focuses on environmental and occupational health effects and is therefore written to those who are not experts in occupational health issues.

Toxicology

Toxicological research efforts on the health effects of nanoparticles have involved both in vitro exposures to cell cultures and in vivo exposures to animal subjects. Initial work in this area grew out of studies conducted to establish the toxicity of ambient ultrafine particles.^2–4 The work by Oberdörster and colleagues was among the first to establish the toxicity of nanoparticles especially in regards to their ability to translocate from the lungs to other organs,^5,6 and the significance of particle surface area concentration as a valid dose metric for nanoparticle toxicity.⁷

Other research groups, for example Grassian et al.,^8–12 Castranova et al.,^13–16 and Donaldson et al.,^17–20 have focused specifically on nanoparticles that are produced in commercial quantities and may pose a threat to workers. In general, these studies suggest that,

(a) smaller particles can be more toxic than larger particles on a per mass basis;

(b) for some nanoparticles, reactivity is better associated with particle surface area rather than count or mass concentration;

(c) inhalation of nanoparticles can lead to oxidative stress and a subsequent chain of events that produce adverse health effects; and

(d) physicochemical characteristics, especially surface functionalization and dissolution rate (in lung surfactant) are significant determinants of nanoparticle toxicity.

A recent summary of the findings from the new field of nanotoxicology is provided by Castranova.²¹

Current guidance

The toxicological studies published to date suggest that concern for the health of workers exposed to nanoparticles is justified. As a potential hazard, these studies contribute information to the overall risk of nanoparticle inhalation expressed as:

risk = hazard × exposure

As will be further explained, the exposure aspect of this equation can be obtained from field studies involving measurements taken at nanoparticle production companies. Likewise, potential emissions from production processes can be estimated to calculate resulting nanoparticle concentrations in production plant work areas. However, it is primarily from results obtained from nanoparticle toxicity studies that guidance values have been proposed as limits on nanoparticle concentration levels in workplaces.

There are various types of exposure limits ranging from those recommended by an ad hoc group, referred to as an occupational exposure limit (OEL), or those from an agency such as the National Institute for Occupational Safety and Health (NIOSH) which publishes recommended exposure limits (RELs), and the Occupational Safety and Health Administration which promulgates enforceable permissible exposure limits (PELs). A group representing academia, industry, and government convened in 2009 to establish a strategy for assessing workplace exposures to nanomaterials. The group evaluated toxicological information and recommendations by other groups, most notably the British Standard Institute,²² to develop generalized OELs based on nanoparticle type and existing exposure limits (ELs) set for similar micro-sized substances:

(a) nanoparticle OEL = 0.066 × EL for insoluble or poorly nanomaterials (for example, titanium dioxide),

(b) nanoparticle OEL = 0.50 × EL for soluble nanomaterials, and

(c) nanoparticle OEL = 0.1 × EL for carcinogenetic, mutagenic, asthmagenic or teratogenic nanomaterials.

The exception is the OEL established for fibrous nanomaterials of 0.01 fibers per mL, which is based on the current OEL for asbestos removal activities.

Since 2010, NIOSH has published two guidance documents that put forth two RELs for titanium dioxide (TiO₂)²³ and a single REL for all carbon nanotube (CNT) and carbon nanofiber (CNF) types.²⁴ These are the first United States (US) agency ELs related to nanoparticles and are based on a thorough review of relevant toxicological data. The TiO₂ REL is divided into an EL for fine TiO₂ of 2.4 mg m⁻³ and an EL for ultrafine TiO₂ of 0.3 mg m⁻³, where “fine” was defined as all particles collected with a respirable dust sampler which has a 50% collection efficiency for 4 μm particles. The agency also states in the report that “ultrafine TiO₂ is a potential occupational carcinogen.” This assessment was principally based on research by Heinrich et al.²⁵ who performed a chronic animal inhalation study with ultrafine TiO₂ and found a significant elevation in adenocarcinomas over that of the control group, and deviates from the long-standing perception that TiO₂ was nothing more than a “nuisance” dust. A similar long-term toxicological study to determine the carcinogenicity of CNTs has not yet been conducted. Therefore NIOSH based its REL for CNTs and CNFs of 7 μg m⁻³ on available short-term animal dose–response data that indicate early stage fibrotic and inflammatory lung response. As with all RELs, the limit value is based on exposure over a working lifetime (40 h work week, 50 weeks per year for 45 years). In a sense, NIOSH made this limit as low as possible while still measurable as the recommended sampling method involves measuring elemental carbon as a surrogate for CNT concentration for which the limit of quantification of the method is 7 μg m⁻³.²⁶

Exposure assessment

One notable aspect of the NIOSH CNT REL is that the metric used, mass concentration, is different for that of another hazardous fibrous aerosol, asbestos, which is enumerated as a count concentration.²⁷ In its guidance document, NIOSH admits that “exposure metrics other than airborne mass concentration may be a better predictor of certain lung diseases,” but decided on a mass concentration because the toxicological effects observed are based on a mass dose and a reasonable existing sampling method reports in mass concentration.²⁴

The issue of the proper metric for enumerating nanoparticles in workplaces is currently debated.²⁸ As mentioned, surface area concentration has been found to correlate well, regardless of particle size, with pulmonary response.⁷ However, this may not be true for all particle types and may also be a function of agglomerate state. As will be explained in more detail below, nanoparticles exist in a workplace atmosphere as either loose or tight bundles of primary particles (Fig. 1). For example, Grassian et al. exposed mice to TiO₂ from two powder sources that differed by their primary particle size: 21 nm and 5 nm.¹¹ Given a smaller diameter, the 5 nm TiO₂ has a much higher total surface area per mass and therefore should have elicited a greater toxicity if it is a surface-area dependent effect. However, the results did not support that hypothesis as the 21 nm TiO₂ produced a moderate, but significantly, higher inflammatory response in mice. On the basis of electron micrographs of the agglomerates produced, the authors noted that the 5 nm TiO₂ produced very tightly bound agglomerates relative to the loosely bound 21 nm TiO₂ agglomerates, and therefore it was conjectured that the larger particles ultimately presented more surface area per mass than the smaller particles. Furthermore, Pauluhn²⁹ argues that particle volume can be the most important dose metric especially in the case of CNTs that tend to form ball-shaped agglomerates that will lack density (and therefore mass) but will nonetheless contribute to the well-known problem of particle overload³⁰ whereby alveolar macrophages attempting particle clearance are overwhelmed by the total volume of particles present in the pulmonary region of the lungs.

Fig. 1 Example of a loose agglomerate (21 nm TiO₂, top) and tight agglomerate (20 nm SiO₂, bottom).

Nanoparticle measurement methods

Given exposure limits that are largely expressed as a mass concentration and the interest by toxicologists in surface area concentrations, research efforts to evaluate work settings in nanoparticle or nanomaterial production facilities (as well as other scenarios down to the level of the university laboratory) are often conducted with multiple sampling instruments designed to capture those two metrics as well as count concentration. These instruments fall into two general categories: “time-integrated” and “direct reading”. Time-integrated measurements involve those which require the completion of a sampling duration after which an analysis is made to determine aerosol concentration, whereas direct-reading instruments provide concentration values in “real time” and typically employ a digital memory device to store the measurements taken for subsequent display and mathematical analysis. The time-integrated devices – primarily filter collection methods – have been used for decades to determine the threat caused by dusts containing, for example, asbestos and silica, whereas direct-reading devices have become more accurate and therefore more often used over the past 20 years. An important consideration when developing these instruments is their portability as they are often intended for “personal” sampling and thus have to be worn by a worker while performing their duties. Larger instruments can be employed for “area” sampling but still must be portable and rugged enough for field studies in often harsh occupational environments.

Time-integrated sampling

Originally, time-integrated aerosol sampling was divided into two general classes by NIOSH: a “total” dust sample, and “respirable”.^31,32 In 1994, international agreement was reached on the nature of the efficiency curves that define the ability of particles of varying sizes to aspirate into the human mouth (inhalable), penetrate below the larynx and into the tracheobronchial region (thoracic), and penetrate down to the alveolar region (respirable). The mathematical models associated with each of these three size ranges (Fig. 2) is published each year by the American Conference of Governmental Hygienists (ACGIH).³³ Once these curves were established, “size-selective” instruments were developed to have collection efficiency curves closely matched to the defined curves. For example, respirable particles constitute the subset of all particles in the atmosphere such that 50% are below 4 μm, and therefore a sampler with the same collection efficiency will collect 4 μm particles with 50% efficiency. In the context of sampling for nanoparticles, however, Fig. 2 demonstrates that all three curves converge for particles <1 μm meaning that size-selective sampling via gravimetric analysis of samplers designed with any one of these efficiency curves is an irrelevant concept when attempting to sample for nanoparticles exclusively since all particles <1 μm will be collected with the same efficiency. Recent efforts are focused on establishing a nano-related sampling curve and associated sampling device. One of the most promising was recently developed by Peters et al.³⁴ They developed a portable gravimetric sampling device that utilizes diffusion screens in line with a sharp-cut cyclone that has 50% efficiency at 300 nm with an efficiency curve that closely approximates the efficiency of deposition of particles in the pulmonary region of the lung.

Fig. 2 Filter sampler collection efficiency curves.

Direct-reading instruments

In general, direct-reading instruments fall into two general types: those that provide a measure of aerosol concentration, either mass or number based, and those that determine the aerosol size distribution.³⁵ Available instruments and their respective measurement size range are given in Fig. 3 in addition to the range of measurements available via electron microscopy. The primary criterion of portability for instruments used for evaluating the dispersion of nanoparticles in an occupational setting restricts choices to those that are small, relatively accurate, and relatively inexpensive. Direct-reading instruments that meet that criterion are the optical particle counter (OPC) and condensation particle counter (CPC), which measure a count concentration, the surface area monitor (SAM), which measures surface area concentration, and the aerosol photometer, which measures mass concentration. A brief description is provided below with full details given by Willeke et al.³⁶

Fig. 3 Measurement range of direct-reading instruments (adapted from Pui³⁵).

An OPC provides a count concentration in the size range of 300–20 000 nm. This instruments sizes and counts particles to allow for the determination of both a number concentration and particle size distribution. As a particle passes through a viewing volume of the detector illuminated by a laser it scatters light which is then detected by a photodetector. The electrical pulses generated by the photodetector are converted to counts and the pulse height is related to particle size. These instruments vary with regards to the light source used (laser, white light) and the number of size bins, or “channels”, into which the sized particles are grouped. Like an OPC, a CPC (also referred to as a condensation nuclei counter, CNC) utilizes the light scattered by a particle to detect and count its presence in the gas stream pumped through the instrument. However, the signal received from a nanoparticle is too small to be accurately detected. To compensate for this problem, the aerosol stream is first passed through a volume containing an alcohol-soaked wick held near 40 °C to saturate the stream with alcohol vapors. The stream then passes through a second chamber held near 10 °C which condenses the alcohol on the particles promoting their growth to a size that can be easily detected. Handheld CPCs respond to particles >10 nm with an upper limit near 1000 nm.

Although both the OPC and CPC are relatively accurate and portable, neither can detect the entire distribution of an aerosol expected in an occupational setting that will span both nano- and micrometer-sized particles. The CPC is helpful for detecting particles in the nano-sized range but does not provide a size distribution by separating particles into size bins. Schmoll et al. investigated a technique in which the two instruments are paired to overcome these difficulties.³⁷ As given in Fig. 4, there is some overlap in particle size detected by the two instruments so that the number of particles <300 nm can be calculated by subtracting all OPC counts in the size bins ranging from 300 to 1000 nm from the counts between 10 and 10 000 nm made by CPC. This provides an additional bin of counts between 10 and 300 nm to add to those available from the OPC. With that information, a count size distribution between 10 and 20 000 nm can be developed. Schmoll et al. found this method to accurately reproduce the aerosol size distribution when compared to counts made by a highly accurate counter/sizer, the scanning mobility particle sizer (SMPS). However, the method became more inaccurate as the index of refraction of the particle measured varied from that of the particle used to calibrate the OPC (polystyrene latex spheres), and for aerosols with very small particles such that most of the distribution is in the first 10–300 nm size bin. Fig. 4 provides an example of this scenario.

Fig. 4 Example of CPC and OPC measurement ranges relative to a nanoparticle aerosol size distribution.

Another class of particle counter utilizes the inertial properties of the particles to differentiate their size. These “time-of-flight” instruments accelerate the particles through a nozzle. The larger particles take longer to accelerate and therefore travel for a longer time period between two lasers that are interrupted by the particle triggering a set of photosensors to record the travel time. A commercial version, the Aerodynamic Particle Sizer (APS, TSI Inc., St. Paul MN) has been frequently used in the past for aerosol assessment and research studies.^38,39 The primary advantage when using this instrument is that it reports counts in bins classified by the aerodynamic diameter of the particle. This metric normalizes differences in particle densities and is also the metric used to express diameter by the ACGIH when describing sampling criteria. However, its lower size limit near 300 nm makes it less desirable for assessing nanoparticle exposures except in cases where large agglomerates are expected.

The photometer and aerosol surface area monitor have received less use in publications related to the assessment of the dispersion of aerosol particles in the workplace. Photometers also rely on light scattered from particles but utilize the intensity of light scattered by the entire cloud of particles, along with algorithms that incorporate the density of the aerosol and the known response of the instrument relative to particle size to provide a measure of mass concentration. Although photometers have been used extensively in the past in occupational settings because they are small enough to be carried by a worker,^40,41 use of these instruments to indicate exposures to nanoparticles is limited because their sensitivity declines exponentially with a decrease in particle size below 1 μm.⁴²

Given research that supports the increased reactivity of small particles relative to their surface area, an electronic counter that gives an indication of particle surface area relative to particle diameter may be the optimal detection device when measuring nanoparticles.⁴³ Particles flowing into the instrument are charged by bombardment with unipolar ions in a process known as diffusion charging. The number of ions a particle can carry is dependent on its surface area. Therefore, a measure of the total charge applied to an aerosol stream is directly related to the total surface area of all particles in the stream. Bon and Maynard compared a commercially available diffusion charger with estimates of surface area made with an SMPS and by transmission electron microscopy (TEM) and found good agreement for particles smaller than 100 nm but for larger particles the diffusion charger response varied as diameter to the power of 1.5.⁴⁴ Another surface area analyser developed by TSI Inc. (St. Paul, MN) was found to be proportional to the mobility diameter to the 1.16 power but correlated well if related to typical lung deposition curves and therefore provides an indication of the potential surface area dose received by the lungs.⁴⁵

Nanoparticle characterization

The ability to fully characterize the chemical and physical properties of nanoparticle surfaces is very important for detailing the potential adverse health effects they may cause. At the most basic level, a morphological and size assessment can be obtained via microscopic methods. However, these assessment methods require both an accurate particle capture method as well as methods needed to adequately characterize particle size and morphology with the microscope. One technique for collecting nanoparticles for analysis by transmission electron microscopy (TEM) is to utilize electrostatic precipitation (ESP) onto a TEM grid.⁴⁶ A device for this purpose was developed by Morrow and Mercer⁴⁷ and characterized by Cheng et al.⁴⁸ Miller et al. have developed a hand-held ESP for use during site assessments.⁴⁹ Direct capture onto a TEM grid is attractive because it is easy to implement but particle collection is not 100% efficient for all particle sizes. An alternative method is to collect particles by filtration and then apply a technique to transfer the dissolved filter onto the TEM grid.⁵⁰ Once particles have been collected on a TEM grid, they can be photographed by the microscope and the resulting digital image analysed to determine particle size and shape. Publicly available software (ImageJ, available from the National Institute of Health (NIH)) can be used to determine particle size based on a variety of diameter types.

Agglomeration

An important aspect of nanoparticle characterization is its agglomeration state. Although manufacturers can produce powders with primary particles that satisfy the definition of a nanoparticle, they quickly coalesce into bundles referred to as agglomerates (weakly bonded) or aggregates (strongly bonded).¹ The speed by which they bond together can be on the order of microseconds for nanoparticle aerosols and is dependent on the aerosol concentration and primary particle size.⁵¹ In some cases, agglomerates are composed of small aggregate groups. As explained by Gray and Muranko, acinoform (grapelike) aggregates result when the spherical primary particles produced from nucleation and coagulation of a supersaturated fluid stick together by van der Waal's forces and are further welded together by the deposition of more material from the fluid phase.⁵² These aggregates can then combine to form larger agglomerates, but they cannot be broken down further than the fused primary-particle-aggregates given applied external forces (such as from sonication).

An agglomerate “state” is not well defined; often characterized in the literature in the qualitative sense of being “loose” or “tight”. To quantify agglomeration state, Powers et al. suggest that an “average agglomeration number” can be derived from the ratio of the volume-based median particle size to the average equivalent spherical volume derived from BET gas adsorption (where “BET” is the first initial of the family names of the three scientists who developed the method).⁵³

Agglomerates have also been characterized in terms of their “fractal” geometry. For example, Virtanen et al. provide a method for determining an agglomerate's “effective density” related to particle mobility and mass, and a “fractal dimension” that depends on the number of primary particles relative to the size of the agglomerate using measurements made with an SMPS and an electrical low-pressure impactor (ELPI).⁵⁴ In an excellent description of methods used to quantify the agglomerate state using fractal analysis from TEM images, Kanniah et al. emphasize the use of a fractal dimension to illustrate aggregate growth mechanisms and agglomerate surface chemistries, whereas lacunarity (a measure of “gappiness” and image inhomogeneity) can be used to assess the colloidal stability once nanoparticles become inhaled and therefore has relevance for dose estimates.⁵⁵

The implications of nanoparticle agglomerate state on toxicity are currently under investigation. In addition to the Grassian et al. study that compared TiO₂ particles of different sizes and agglomeration states,¹² other research teams have performed exposure studies to reveal whether nanoparticle structure affects toxicity.^56–59 For example, Lankoff et al. performed an in vitro study in which different cell lines were challenged with silver and TiO₂ nanoparticles with different agglomeration states.⁵⁷ They discovered the rate by which nanoparticles are taken up by cells through mechanisms such as macropinocytosis and phagocytosis differs by cell type and is therefore not strictly related to particle size, but is based on a more complex relation of both particle and cell properties.

Elemental speciation

In addition to determining the morphological characteristics of nanoparticles, a wide variety of methods are available to characterize their surface properties and chemical composition with the use of electron microscopy. Many of these methods are summarized by Maynard.⁴⁶ Once a sample is captured onto a TEM grid, characterization methods associated with electron microscopy such as electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDX or EDS) can be used to identify particle elemental species. This method allows for a chemical speciation approach to an investigation on the sources of nanoparticles that have dispersed into a workplace similar to those applied to source tracking of ambient pollutants. A field-portable instrument is also available that will provide particle elemental speciation – the field portable X-ray fluorescence monitor (FPXRF) – that has found increasing use in place of TEM analysis for nanoparticle aerosol characterization because of its portability and low-cost relative to multiple TEM analyses.^60,61

In certain occupational settings involving the production of nanoparticles, a nanopowder will be a known product and available for bulk analysis. For example, it has been shown that the degree of crystallinity of nanopowders such as titanium dioxide is important because it can affect cytotoxicity and inflammatory response.⁶² A common method for determining crystallinity is by X-ray powder diffraction (XRD).¹² If a bulk sample is available, the surface area relative to the mass of the sample can also be determined by BET analysis. Likewise, surface chemical properties from a bulk sample can be determined by X-ray photoelectron spectroscopy (XPS) and the identification of surface functional groups can be obtained via attenuated total reflection-fourier transform infrared (ATR-FTIR) spectroscopy.^63,64 Due to the sophistication of these instruments and their expense, utilizing these methods for characterizing nanoparticles will necessarily involve the aid of a research facility or company specializing in powder characterization techniques.

Dustiness

A nanoparticle characteristic that is specifically related to occupational exposures is the dustiness of the dry nanopowder. The premise for this powder quality is that the risk of exposure to aerosolized nanoparticles increases with the propensity of the bulk powder to produce airborne dust as a consequence of handling the powder. Various instruments have therefore been developed to quantify the dustiness of a powder by mimicking handling scenarios that may produce airborne dust such as when storing, conveying, or mixing the bulk powder.^65–67 Methods to evaluate the dustiness of a powder have not been standardized in the United States but a standard developed in the United Kingdom and adopted by the European Committee for Standardization (CEN) has been widely accepted for testing the dustiness of powders that are relevant to potential occupational exposures.⁶⁸ This standard describes two methods to quantify dustiness: a rotating drum mixes the powder and air flow through the drum is captured onto filters; and a vertical column with a hopper of powder located at the top which continuously drops powder down through the column as upward moving air is pulled out of the column through filters to collect the aerosolized dust with samplers to obtain the respirable and inhalable dust fractions. The measured value is mass of dust captured per mass of dust (mg kg⁻¹) applied to the tester. Rather than remain as a continuous variable, the writers of the standard suggest that the dustiness value obtained be placed in one of four dustiness categories: very low, low, moderate, and high. The application of categories avoids issues that arise due to the large differences between powder types (several orders of magnitude) and the lack of precision between measurements of the same powder.⁶⁹

The primary drawback to either method described in the CEN standard is the large quantities of powder (g min⁻¹) required that precludes their use when evaluating the dustiness of expensive nanopowders. Several attempts have been made to modify the standard methods, or develop new methods, to measure dustiness with low powder quantities.^70–72 Boundy et al. developed an apparatus primarily for the evaluation of pharmaceutical powders that injects a 50 mg bolus of powder into a 5.7 L glass jar and the exit air is captured on filters for weighing.⁷² Schneider and Jensen adapted the rotating drum method by reducing the volume of the drum so that only 2 g of powder was needed.⁷¹ They also utilized an APS to record the number concentration and size distribution of the aerosolized powder exiting the drum. The mass of dust exiting the drum was therefore computed from the size distribution and assuming spherical particles with a known density. In a similar manner, O'Shaughnessy et al. modified the continuous drop apparatus by installing a ball valve on top of the column to provide a single bolus of powder of 15 mg.⁷⁰ A cross-stream airflow pulled air through a filter, into the bottom of the column and into an APS to determine the respirable mass of the resulting aerosol. Of the 10 nanopowders tested with this device, amorphous SiO₂ resulted in a significantly higher dustiness than all other powders tested which included TiO₂, single-walled carbon nanotubes, and copper nanopowders. For example, SiO₂ has a moderate mass density of 2.2 g cm⁻³, but very low bulk density of 0.03 g cm⁻³ that made the powder very “fluffy” and therefore highly dusty (Fig. 5). A relation between primary particle size and dustiness was found when three grades of TiO₂ were evaluated where reagent-grade TiO₂ with primary particles between 100 and 200 nm was compared to 21 nm TiO₂ and 5 nm TiO₂ with resulting dustiness values of 18.2 mg kg⁻¹, 45 mg kg⁻¹, and 60 mg kg⁻¹, respectively.

Fig. 5 SEM images of TiO₂ (top) and SiO₂ (bottom) powder.

Workplace nanoparticle assessments

In general, the worst-case scenario for enhancing the risk of exposing workers to nanoparticles is during the manufacture of nanoparticles in the dry state. The resulting powder may be dispersed indoors during the production, capture and packaging stages. Other work tasks and scenarios that can result in worker exposure to nanoparticles are: pouring or mixing a liquid suspension containing nanoparticles where a high degree of agitation is involved; generating nanoparticles in non-enclosed systems; maintenance or clean-up of equipment used to produce nanoparticles; cleaning dust collection systems and ventilation ducts through which nanoparticles travel; and disrupting nanomaterials by machining, sanding, and other abrasive activities.⁷³

An overview of nanoparticle production methods that may result in the dispersion of nanoparticles in a workplace is given by Aitken et al.⁷⁴ These methods fall into three main groups: gas phase processes such as flame pyrolysis; vapor deposition synthesis; and colloidal or liquid phase methods which lead to the formation of colloids. For example, carbon nanotubes (CNTs) are typically produced via chemical vapour deposition (CVD) often with a catalyst to reduce the high temperatures needed for CNT synthesis.⁷⁵ Aitken et al. also add a fourth method, mechanical processes such as grinding, milling, and alloying, but admit that these attrition methods contrast with the other three groups because they constitute a “top-down” approach rather than the “bottom-up” methods more typically associated with modern engineered nanoparticle production.

The first investigation of nanoparticle exposures in the United States was conducted in 2004 by Maynard et al.⁷⁶ The study team investigated CNT processing in both a laboratory setting and at several CNT production facilities. Several novel assessment methods were utilized in this study. To minimize background particles, the study team built a plastic tent around an area where CNT was handled and filtered air was used to flush out particle-laden air before measuring while CNT handling occurred. The CNT fabrication process, high-pressure carbon monoxide (HiPCO), involved the production of iron and nickel ultrafine particles as catalysts that are released into the air along with CNT particles when handling the product powder. Therefore, to discriminate between CNT particles and other carbon-containing particles, the team analysed for iron and nickel and calculated the CNT concentration knowing the ratio of catalyst to CNT particles. With this method they estimated CNT concentrations varied between 0.7 and 53 μg m⁻³. At the time of this study, the authors did not have sufficient toxicological data to relate their measurements to potential health effects.

Production facility assessments

Since the Maynard et al. study results from an additional nine studies have been published in peer-reviewed journals that detail efforts to assess engineered nanoparticle aerosol concentrations in commercial nanoparticle production facilities.^77–85 A summary of information provided in these articles is given in Table 1 where, for comparison sake, the reported mass concentrations are provided regardless of other metrics sampled unless only particle count was sampled. The relatively small number of site assessments may be attributed to the difficulty obtaining permission to enter plants given the proprietary nature of the fabrication process. To offset this problem, several studies were conducted to reproduce nanoparticle production processes or the release of nanoparticles from nanomaterials in a research setting.^86–89 Furthermore, some exposure assessment studies focused on releases in laboratory settings.^90–93

Table 1 Summary of selected nanomaterial concentration ranges from exposure assessment studies at commercial nanomaterial production facilities

Ref.	Sampling type and process	Nanomaterial	Metric	Maximum concentrations	Notes
76	Personal: during vessel removal and handling	CNT	Mass	53 μg m^−3	Mass of CNT inferred from mass of Ni and Cu
77	Area: in CNF processing areas	CNF	Mass	32 μg m^−3	Mass of respirable elemental carbon
78	Area and personal: production and handling	TiO2	Mass	8 μg m^−3	Mass of dust determined then TiO2 by ICP.
79	Area: production and handling	Metal-based nanostructures	Mass	1340 μg m^−3	Concentrations measured with a photometer
80	Area: transfer from dryer to collection vessel	CNF	Mass	1100 μg m^−3	Concentrations measured with a photometer
81	Area: bagging operation	Fullerenes	Count	3.0 × 10^4 cm^−3	Counts for diameters <50 nm
82	Area: reactor cleanout	Metals	Mass	6700 μg m^−3	Maximum concentration measured for silver nanoparticles
83	Area: opening hatch after production	Silver	Count	18.9 × 10^6 cm^−3	Counts for diameters 10–250 nm
84	Area: material handling	Lithium titanate	Mass	118 μg m^−3	Mass calculated from counts made with a CPC and OPC
85	Area: fume hood housing arc reactor	Fullerenes	Mass	150 μg m^−3	Concentrations measured with a photometer

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As indicated in Table 1, a majority of the studies utilized direct-reading instruments to assess exposure. These instruments allow an analysis of the transient behaviour of nanoparticle concentrations over time, especially when investigating the many short-term tasks associated with nanoparticle production. The negative aspect of their use is that they will not be as accurate as a filter-based gravimetric sample taken over a longer time period. For example, if an OPC is used then mass concentration is inferred from the assumption that the particles are spheres with a volume dictated by the median diameter of each size bin and that the aerosol mass density is known, both of which may be inaccurate. Likewise, if an aerosol photometer is used then particle density must also be known and the response of the instrument can change with a change in size distribution even when mass concentration remains constant.⁹⁴ This may occur as a photometer is moved away from an aerosol source where particles change from many small agglomerates to fewer large agglomerates.

Assessment strategies

The issue of measurement accuracy is compounded by the relatively low concentrations obtained from the studies summarized in Table 1 compared to traditionally dusty occupations such as mining and woodworking where concentrations are typically in the mg m⁻³ range (the OSHA PEL for coal and wood dust is 2.4 mg m⁻³ and 15 mg m⁻³, respectively). These low concentrations can often be comparable to “background” levels, either those measured in the ambient air or in clean areas of a manufacturing facility such as office space. Methner et al. suggest using TEM to distinguish the constituents of background air relative to air to be measured in a production facility to confirm that engineered nanoparticles are present then using background measurements to adjust those measured in production areas.⁸² This combination of direct-reading instruments with TEM morphological and chemical characterization of nanoparticles constitutes the basis of the Nanoparticle Emission Assessment Technique (NEAT) advocated by NIOSH.⁹⁵

The NEAT method was used by Peters et al. when investigating exposures that created a nanomaterial from lithium titanate.⁸⁴ From the TEM images obtained at the plant, they were able to distinguish several morphological types from a large (>1 μm) spherical particle, to small (<200 nm) chain aggregates. With the application of TEM-EDX the research team was able to determine that the large spheres were composed of tightly agglomerated lithium titanate primary particles whereas the small aggregates were most likely present because of a welding operation going on in the plant during the sampling. The use of a CPC and OPC during a hopper filling operation confirmed that this nanomaterial operation was producing micrometer-sized particles: the CPC measurements remained relatively constant whereas the OPC concentrations fluctuated in sync with the filling cycle. This study, therefore, provided a good example of the use of the NEAT process but also provided evidence that the nanomaterial production may not necessarily result in engineered nanoparticles.

Current initiatives

Long-term studies

From an occupational standpoint, the primary goal of research to evaluate an exposure hazard is the protection of workers' health. That goal is attained through a combination of studies that ultimately determine the hazard and the exposure in order to understand the risk from which exposure limits to protect workers can be developed. Nanotechnology at the industrial level is not much more than a decade old, but already enough site assessments have been accomplished to obtain data needed to assess exposure. The maximum concentrations shown in Table 1 indicate a wide range. However, they do not necessarily indicate exposure as typically defined for occupational settings as being the time-weighted average concentration over an 8 h workshift. Therefore, long-term studies are needed with the use of personal measurement devices to more accurately assess exposure in nanomaterial facilities.

Future long-term exposure studies should necessarily be linked to an epidemiological investigation that incorporates measures of all probable risk factors for health among nanomaterial workers. The lack of evidence from population-based studies is perhaps the most surprising aspect of nanomaterial worker health information to date. It is not surprising that an epidemiological investigation has not be done, but that health science has advanced to the stage that recommended exposure limits can be put forth without even moderate numbers of cases reported. The proactive aspect of this research is commendable in that regard: adverse health effects can be averted based exclusively on lab-based toxicological research.

Exposure metric

For the foreseeable future, it appears that mass concentrations will be the most valuable metric. When considered from a toxicological viewpoint, the ultimate criterion of exposure is the dose of the contaminant received. Therefore, exposure concentration is ultimately a surrogate for dose once it is determined that a certain concentration provides a certain dose (to an adult working 8-hour per day) above which ill-health effects become evident either on an acute or chronic basis. The relationship between mass concentration and dose, on a mass/body-mass basis, is therefore more straightforward than when relating surface area or count concentrations to mass dose. Regardless, given particle interactions in the lung which are surface-area dependent, and the ease by which nanoparticle counts can be obtained, research to link the other two metrics to health effects is also needed. This effort would be stimulated by toxicological investigations that report as many metrics as possible, especially when performing “whole-body” inhalation exposures involving aerosolizing nanoparticles. The minimum requirement is one metric plus size distribution from which the other metrics could be calculated. With this information a count-based and surface-area-based dose could also be calculated to further efforts to link those metrics to human health.

High-throughput screening

The worry among industrial hygienists tasked with protecting the health of workers in nanotechnology companies is that a new nanomaterial will be developed that will have drastic health effects. The historical precedent, of course, is asbestos which was liberally applied by unprotected workers for decades before the chronic effects became evident. As material scientists become more adept at manipulating nanostructures, there is a concern that a functional group attached to a CNT, for example, may change its properties from a benign to toxic compound. The many congeners of polychlorinated biphenyls (PCBs), some of which are much more toxic than others, is a precedent for this fear. Therefore, “high throughput” nanomaterial screening techniques are needed to quickly and accurately assess the potential toxicity of nanomaterials. Work in this area is presently underway.^96–98 For example, Damoiseaux et al. provide a framework for a toxicity screening process for nanomaterials that involves up-front characterization steps followed by toxicological screening that includes assays to determine oxidative stress potential and other in vitro assessments for toxicity that can be performed in a way to yield results in days or weeks rather than months for inhalation studies.⁹⁷

Instrumentation

As alluded to previously, exposure studies that involve count concentrations have required the combination of two instruments, a CPC and OPC, to evaluate across the range of expected particle sizes in a workplace. The limitation of this method is that the real interest is at the nano-level for which only a few, relatively large size bins are available. The bench-scale SMPS overcomes this problem but is not easily transportable. An SMPS consists of two devices, a CPC and a differential mobility analyzer (DMA). A DMA is an ingenious device that separates nanoparticles by size as they flow past a charged column. For a given voltage, only one particle size exits the DMA that are then counted by the CPC. Scanning across a voltage range allows for the enumeration of particles of different sizes and thus recreate the aerosol size distribution. To reduce its size the DMA has been reconfigured with a radial design. The radial DMA was developed in the previous decade but did not find much use because it cannot distinguish particle sizes to the level of the bench-scale, column-based DMA.^99,100 However, this device can be packaged with a hand-held CPC to create additional size bins useful for recreating nanoparticle size distributions while performing site assessments. Some instrument manufacturers are currently developing an instrument of this type, which in combination with small cyclones capable of sampling only sub-micrometer particles,³⁴ will provide both nanoparticle count and mass concentrations. Furthermore, Maynard and Aitken provide specifications for a “universal aerosol monitor” that would expand on the need for measuring multiple metrics at the nano-level as well as being portable, preferably to the level of being personally wearable, time-resolved, and with data-logging capabilities.¹⁰¹

Modelling and analysis

Another important area of future research involves the development of conceptual models useful for evaluating and establishing risk scenarios involving nanoparticle exposures. Models of this type, such as the one described by Schneider et al. can be used as a base-level assessment process for evaluating exposure scenarios.¹⁰² The model is developed from a source characterization and incorporates particle coagulation and scavenging equations to simulate source-to-receptor changes in the dispersed powder and resulting nanoparticle aerosol. Future work in this area would be valuable for simulating exposure scenarios especially when linked to improved particle characterizations, such as powder dustiness, and sources identified to be potential nanoparticle emitters.

Advances in statistical analysis of exposure data have also been made with special emphasis on data streams from direct-reading instruments used to assess nanoparticle exposures. As it has become apparent from recent assessments in nanoparticle production facilities, the use of direct-reading instruments provides important information related to both the quantity and size of nanoparticles that may pose a health threat to workers. However, a series of real-time measurements obtained by, for example, a CPC do not represent a collection of independent random values that can be used to statistically compare different locations within a facility. Such measurements tend to be autocorrelated which violates the proper of use of statistical comparison techniques such as a t-test. Entink et al.¹⁰³ describe a method for properly statistically analysing real-time data by first filtering each data series with the use of the Box–Jenkins autoregressive integrated moving average (ARIMA) models.¹⁰⁴ By creating a model to describe the autocorrelation structure of each dataset, the autocorrelation can be nullified prior to the application of a t-test.

Conclusion

The first international symposium devoted to the occupational health implications of nanomaterials was held in Buxton, England in 2004. At that time, research devoted to protecting workers in the nanotechnology industry was in its infancy and yet in the eight years since that conference a remarkable level of scientific effort has been expended on this subject. The questions that immediately arose were those dealing with the fundamental aspects of research in this area, including whether nanoparticles possessed novel properties that would give rise to previously undocumented health effects. The evidence gathered to date suggests that nanoparticle toxicity is particle-dependent as well as dose-dependent, with certain nanoparticle types, for example carbon nanotubes, capable of eliciting health effects that warrant the establishment of safeguards for workers. Early research was also based on whether entirely new assessment methods and instruments are needed. Traditional occupational exposures to dusts, with a few exceptions, involved particles large enough to develop a measurable mass when collected on a filter. It is clear from the literature that accurate measurement of nanoparticles with instruments capable of enumerating particles using multiple metrics as well as techniques to distinguish incidental particles from engineered nanoparticles is needed to fully characterize workplace nanoparticle exposures.

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